Learning Framework for Multi-Agent Simulation of Supply Chain Systems

Abstract

Multi-agent System (MAS) is becoming a popularand useful method applied to solve problems in supply chains under dynamic environment. The learning ability is one of the most important components for "intelligent" agents. It helps agents adjust to dynamic environment more quickly and gain experience for making decisions. This paper proposes a learning framework for multi-agent simulation of supply chain systems. And this framework is explained step by step in 4 levels: individual, department, organization and supply chain system. The validity of such framework is established by simulating an example learning method using the simplified version of the framework. Furthermore, the application of such framework is not limited for SC, but also for community, government etc.